A macro-cell statistical location estimation method for TD-SCDMA networks

TD-SCDMA is an innovative wireless radio standard for a physical layer 3G air interface, approved as one 3GPP standards by ITU in May 2000. Based on the unique advantages of the physical layer, this paper investigates network-based methods to obtain the angle of arrival (AOA) and time of arrival (TOA) via subspace tracking and channel impulsive estimation. By incorporating the spatial–temporal channel of radio propagation, this paper proposes a unified objective function to extract mobile location information from the statistical distribution of AOA and TOA data in a TD-SCDMA cellular network. The proposed method may estimate mobile position even using one base station. The location performances are analyzed in detail in macro-cell scenarios. This method can be easily extended to other networks except TD-SCDMA, provided that the statistical information of the local radio propagation channel is available as pre-knowledge. Simulation comparing several hybrid location methods in two macro-cell scenarios show that the proposed method has a high accuracy; but it has a relatively high complexity.